Effect of public health expenditure on health status in Ghana

Abstract

Health is an outcome indicator of economic growth and development of a country. Healthcare is a major factor for health status. In this regard, healthcare expenditure is a vital input for the health production function. In this context, this study examined the effect of public health expenditure on health status in Ghana. Annual time-series data on infant mortality rate, real per capita income, literacy levels and female labour force participation rate for the period 1990-2012 have been used. Infant mortality rate was used as the output variable. To test the relationship between input-output variables, Ordinary Least Squares and Newey-West regression techniques were used. The regression estimates suggest that real per capita income, public health expenditure, education and female presence in the labour market were negatively related to infant mortality rate. However, the elasticity coefficients of female participation in the labour market and real per capita income were statistically insignificant at 5% level. This study concludes that public health expenditure and literacy/education improve health status by reducing infant mortality. The favourable effect of education or literacy on health is greater than that of public health spending whereas the effect of real per capita income on health was found to be weak. The findings provide the impetus for government to raise literacy level and its health spending in the country to promote health.

Public Health Expenditures and Health Outcomes: New Evidence from Ghana

“…Finally, the study attempts to quantify the monetary cost of averting (one) extra death and extra life year gained to the government. Some of these issues were unaddressed in previous studies on Ghana (see Boachie and Ramu 2016;Compah-Keyeke et al 2013) and similar studies on the theme (Novignon et al 2012;Mohapatra 2016).…”

“…In 2014, for example, only 6.82% of total government expenditure went into health, a fall in previous allocations and below the proposed 15% target under the Abuja Declaration. In this respect, extending the studies by Boachie and Ramu (2016) and Compah-Keyeke et al (2013) to re-examine the health effect of public health expenditures in Ghana is important. It would establish the role of government in improving health conditions towards achieving the third goal under the Sustainable Development Goals (SDGs) by 2030.…”

“…We conduct our analysis for Ghana because few studies have explored the relationship between public health expenditures and health outcomes in Ghana. Two earlier studies on Ghana produced conflicting results, perhaps due to their smaller sample sizes, and were unable to address potential endogeneity issues (see Compah-Keyeke et al 2013;Boachie and Ramu 2016). Besides, health status remains low due to high malnutrition, morbidity, and mortality (especially maternal and child mortality) compared to the global average.…”

Public Health Expenditure and Health Outcomes in Nigeria

“…Both public and private healthcare spending showed strong positive association with health status even though public healthcare spending had relatively higher impact. Boachie and Ramu [2015] examined the relationship between public health expenditure and health status in Ghana. In their study, they examined the impact of public health spending on health status for the period 1990-2002 employing standard OLS and Newey-White estimation technique.…”

Per capita income and public health expenditure: what makes good child health outcomes in Tanzania? a comparison of Frequentist and Bayesian approach (1995-2013)

“…The reason for incorporating the Bayesian analysis is to get reliable estimation results when a researcher doubts about endogeneity and also to address the problem of sample size and simultaneity bias experienced in previous research and to find whether different methodologies and sample size results to different relationship. Frequentist approach intended to compare the low ill-power problems due to small data sets as argued by Dieleman, (2013) and other researchers using small data sets of less than 30 observations (Anand & Ravallion, 1993, Hojman, 1996, Boachie et al, 2016 for example used small sample sizes of 22 observations, 10-20 observations, and 22 observations respectively. The advantage of the Bayesian approach over the frequentist is to estimate parameters based upon observed data by simulating a small sample using Markov Chain Monte-Carlo (MCMC) getting up to 10,000 samples to give posterior distribution, which can provide stronger statistical power.…”